Sounds impossible, right? The saying goes that you can never be too rich or too thin or have too much memory.

However, there is one good indication that your SQL Server is probably overprovisioned, and to explain it, I need to cover 3 metrics.

1. Max Server Memory is set at the instance level: right-click on your SQL Server name in SSMS, click Properties, Memory, and it’s “Maximum server memory.” This is how much memory you’re willing to let the engine use. (The rocket surgeons in the audience are desperate for the chance to raise their hands to point out different things that are or aren’t included in max memory – hold that thought. That’s a different blog post.)

2. Target Server Memory is how much memory the engine is willing to use. You can track this with the Perfmon counter SQLServer:Memory Manager – Target Server Memory (KB):

SELECT *
FROM sys.dm_os_performance_counters
WHERE counter_name LIKE '%Target Server%';

Generally, when you start up SQL Server, the target is set at your max. However, SQL Server doesn’t allocate all of that memory by default. (Again, the experts wanna raise hands and prove how much they know – zip it.)

3. Total Server Memory is roughly how much the engine is actually using. (Neckbeards – seriously – zip it until the end of the post. I’m not playing.) After startup, SQL Server will gradually use more and more memory as your queries require it. Scan a big index? SQL Server will start caching as much of that index as it can in memory. You’ll see this number increase over time until – generally speaking – it matches target server memory.

SELECT *
FROM sys.dm_os_performance_counters
WHERE counter_name LIKE '%Total Server%';

What if Total Server Memory doesn’t go up?

Say you have a SQL Server with:

• 64GB memory
• Max memory set to 60GB
• 1GB of total database size (just to pick an extreme example)

Infrequent query workloads (we don’t have hundreds of users trying to sort the database’s biggest table simultaneously, or do cartesian joins)

SQL Server might just not ever need the memory.

And in a situation like this, after a restart, you’ll see Total Server Memory go up to 2-3GB and call it a day. It never rises up to 10GB, let alone 60GB. That means this SQL Server just has more memory than it needs.

Here’s an example of a server that was restarted several days ago, and still hasn’t used 4GB of its 85GB max memory setting. Here, I’m not showing max memory – just the OS in the VM, and target and total:



In most cases, it’s not quite that black-and-white, but you can still use the speed at which Total Server Memory rises after a reboot to get a rough indication of how badly (and quickly) SQL Server needs that memory. If it goes up to Target Server Memory within a couple of hours, yep, you want that memory bad. But if it takes days? Maybe memory isn’t this server’s biggest challenge.

Exceptions obviously apply – for example, you might have an accounting server that only sees its busiest activity during close of business periods. Its memory needs might be very strong then, but not such a big deal the rest of the month.

A key part of the SQL Server Agent is the ability to schedule jobs. While you can create one schedule for each agent job, frequently with applications like Reporting Services, users use Shared Schedules across multiple jobs. For instance, you can set a schedule to run at 8 am on week days or run every 2 hours or pick from a predefined list of schedules that already exist in the MSDB database. These are very convenient. However, if you choose to use these be sure you are keeping track of what is running for each of these shared schedules. You should not have everything running at once.

This is an example of a job schedule in a Management Studio SQL Server Agent Job. You can create a new one or pick from a list of already made schedules.

There’s nothing inherently wrong with using shared schedules—some very small operations can all run at the same time, however when you start to use them for larger operations you can really impact the overall performance of your server.

Many times, I have seen high CPU or locks as well as many other performance issues due to the system being overloaded with jobs running on shared schedules or all at the same time (midnight is a frequently common choice). Not every report to should run at 8 am and every data load run every 2 hours. If you not using shared schedules or added a separate schedule per job it is also important to make sure you are not running up against other things running. If you are using applications like SSRS, then you need to pay attention to when the report subscription refreshes are happening. Don’t overload your system by having everything run at once. Job and subscription schedules need to be analyzed and evaluated just like everything else you care for in your database.

To keep this from happening consult your agent jobs to see what other jobs are running before scheduling additional ones. You can easily get a glimpse in Job activity monitor to see what’s running and when it will run next.

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In this post, I will make a Cascading Dropdown in AngularJS. Add 2 Class 1 for Countries and other for state. Write the following code:
public class Country 
{ 
    public int CountryId { get; set; } 
    public string CountryName { get; set; } 
} 
public class State 
{ 
    public int StateId { get; set; } 
    public string StateName { get; set; } 
    public int CountryId { get; set; } 
} 

Create a ActionResult Name it as Index [Add a View].

Add the script

<script src="~/Scripts/angular.min.js"></script> 

Create a js Name it in my case its CascadingDropdown.

var app = angular.module('myApp', []); 
app.controller('myController', function ($scope, $http) { 
    getcountries(); 
    function getcountries() { 
     
        $http({ 
            method: 'Get', 
            url: '/Home/Countries' 
 
        }).success(function (data, status, header, config) { 
 
            $scope.countries = data; 
        }).error(function (data, status, header, config) { 
            $scope.message = "Error"; 
        }); 
    } 
 
    $scope.GetStates = function ()  
    { 
        var countryIdselected = $scope.countrymodel; 
        if (countryIdselected) { 
            $http({ 
                method: 'Post', 
                url: '/Home/States', 
                data: JSON.stringify({ countryId: countryIdselected }) 
            }).success(function (data, status, header, config) { 
                $scope.states = data; 
            }).error(function (data, status, header, config) { 
                $scope.message = "Error"; 
            }) 
        } 
        else { 
            $scope.states = null; 
        } 
    } 
}); 
 
 
//Calls for Country DropDown 
 public ActionResult Countries() 
        { 
            List<Country> cobj = new List<Country>(); 
            cobj.Add(new Country { CountryId = 1, CountryName = "India" }); 
            cobj.Add(new Country { CountryId = 2, CountryName = "Srilanka" }); 
            cobj.Add(new Country { CountryId = 3, CountryName = "USA" }); 
 
            return Json(cobj, JsonRequestBehavior.AllowGet); 
        } 
 
//Calls for State DropDown with CountryID as Parameter 
 
        public ActionResult States(int countryId) 
        { 
   List<State> sobj = new List<State>(); 
   sobj.Add(new State { StateId = 1, StateName = "Karnataka", CountryId = 1 }); 
   sobj.Add(new State { StateId = 2, StateName = "Kerala", CountryId = 1 }); 
   sobj.Add(new State { StateId = 3, StateName = "TamilNadu", CountryId = 1 }); 
   sobj.Add(new State { StateId = 1, StateName = "Newyork", CountryId = 3 }); 
   sobj.Add(new State { StateId = 1, StateName = "Colombo", CountryId = 2 }); 
 
//Filter based on CountryID 
            var result = sobj.Where(x => x.CountryId == countryId).Select(x => new { x.StateId, x.StateName }); 
 
            return Json(result); 
        } 
 
//IndexView 
//  Add the script file <script src="~/Scripts/CascadingDropdown.js"></script> 
<div ng-app="myApp"> 
       
            <form name="mainForm"  ng-controller="myController"> 
 
                <select ng-model="countrymodel" ng-options=" c.CountryId as c.CountryName for c in countries" ng-change="GetStates()"> 
                    <option value="">-- Select Country --</option> 
                </select> 
                <select ng-model="statemodel" ng-options="s.StateId as s.StateName for s in states "> 
                    <option value="">-- Select State --</option> 
                </select> 
            </form> 
</div>  

I hope it works for you!

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To find the ASCII value of an alphabet or a number, we can use ASCII function in SQL Server. We will see how to get the ASCII value of numbers from 0-9 and uppercase and lowercase alphabets.

What is ASCII?
ASCII (American Standard Code for Information Interchange) is the most common format for text files in computers and on the internet. In an ASCII file, each alphabetic, numeric, or special character is represented with a 7-bit binary number (a string of seven 0s or 1s). There can be 128 possible characters defined. It serves as a character encoding standard for modern computers.

Syntax
ASCII ( ‘character_expression’ )

ASCII value of capital A is 65 and Z 90.
    SELECT ASCII('A') 
    SELECT ASCII('Z') 

To find the ASCII values of alphabets from A to Z, use this code.

    DECLARE @Start int 
    set @Start=65 
    while(@Start<=90) 
    begin 
    print char(@Start) 
    set @Start=@Start+1 
    end 

To find the ASCII values of characters from a to z, we can use this query.
    SELECT ASCII('a') 
     
    SELECT ASCII('z') 
     
    DECLARE @Start int 
    set @Start=97 
    while(@Start<=122) 
    begin 
    print char(@Start) 
    set @Start=@Start+1 
    end 

ASCII Values Of Alphabets And Number In SQL Server

To find the ASCII value of numbers from 0 to 9, we can use this query.
    SELECT ASCII(9) 
     
    SELECT ASCII(0) 
     
    DECLARE @Start int 
    set @Start=48 
    while(@Start<=57) 
    begin 
    print char(@Start) 
    set @Start=@Start+1 
    end

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Approximate COUNT DISTINCT

We all have written queries that use COUNT DISTINCT to get the unique number of non-NULL values from a table. This process can generate a noticeable performance hit especially for larger tables with millions of rows. Many times, there is no way around this. To help mitigate this overhead SQL Server 2019 introduces us to approximating the distinct count with the new APPROX_COUNT_DISTINCT function. The function approximates the count within a 2% precision to the actual answer at a fraction of the time.

Let’s see this in action.
In this example, I am using the AdventureworksDW2016CTP3 sample database which you can download here.
    SET STATISTICS IO ON 
    SELECT COUNT(DISTINCT([SalesOrderNumber])) as DISTINCTCOUNT 
    FROM [dbo].[FactResellerSalesXL_PageCompressed] 

SQL Server Execution Times
CPU time = 3828 ms, elapsed time = 14281 ms.
    SELECT APPROX_COUNT_DISTINCT ( [SalesOrderNumber]) as APPROX_DISTINCTCOUNT 
    FROM [dbo].[FactResellerSalesXL_PageCompressed] 

SQL Server Execution Times
CPU time = 7390 ms, elapsed time = 4071 ms.

APPROX_COUNT_DISTINCT Function In SQL

You can see the elapsed time is significantly lower! Great improvement using this new function.

The first time I did this, I did it wrong. A silly typo with a major result difference. So take a moment and learn from my mistake.

Note that I use COUNT(DISTINCT(SalesOrderNumber)) not DISTINCT COUNT (SalesOrderNumber ). This makes all the difference. If you do it wrong, the numbers will be way off as you can see from the below result set. You’ll also find that the APPROX_DISTINCTCOUNT will return much slower than the Distinct Count; which is not expected.

APPROX_COUNT_DISTINCT Function In SQL

Remember COUNT(DISTINCT expression) evaluates the expression for each row in a group and returns the number of unique, non-null values, which is what APPROX_COUNT_DISTINCT does. DISTINCT COUNT (expression) just returns a row count of the expression, there is nothing DISTINCT about it.

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